The Association between Plant-Based Diets and Dietary Patterns with Cardiometabolic Risk in a Sample of Commercial Taxi Drivers in South Africa.

The consumption of unhealthy foods and a sedentary lifestyle predispose individuals to non-communicable diseases. This study investigated the distribution and the association of plant-based diets (PBDs) and dietary patterns in relation to the cardiometabolic risks in commercial taxi drivers. A cross-sectional analysis was conducted among males (≥19 years) who consumed street foods sold by vendors in the Cape Metropole. A validated questionnaire was administered, including a quantified 24 h dietary recall, and fasting blood samples were collected for biochemical analyses. Statistical analyses were performed to investigate the association between dietary habits and cardiometabolic risks, while adjusting for confounding variables. The analytic sample consisted of 189 males with a median age of 38 years. The taxi drivers who ranked in the top-third of the healthy plant-based diet index (hPDI) had a 1-4% lower likelihood of having raised triglycerides (TG). Furthermore, consumption patterns including refined grains and meat conferred a 33% lower likelihood of dysglycaemia (p = 0.049), while fish/seafood, potatoes, and vegetables conferred a 43% greater likelihood of low high-density lipoprotein cholesterol (HDL-C) (p = 0.026) and 44% greater probability of raised low-density lipoprotein cholesterol (LDL-C) (p = 0.027). Consumption patterns, including sugar-sweetened beverages and eggs, conferred a 37% greater probability of hypertension (p = 0.047) and 53% greater likelihood of subclinical inflammation (p = 0.017). These preliminary findings require larger and more elaborate studies to explore the associations between PBDs and dietary patterns in at-risk African populations, with or without sedentary lifestyles, and exposure to unhealthy food environments.

Sociodemographic and lifestyle factors and the risk of metabolic syndrome in taxi drivers: A focus on street food.

Background: In South Africa, similar to other populous countries, the taxi industry is an important form of transportation that contributes to the country's development. As a result, minibus taxi driving is an occupation characterized by strenuous activities such as long hours of driving, limited rest, and challenges related to securing passengers, among several others. Consequently, to combat stress, some commercial drivers resort to smoking, overeating unhealthy food sold at transportation interchange areas (i.e., taxi ranks), and participating in sedentary behaviors. Most of these activities are risk factors for metabolic syndrome (MetS). Aim: Therefore, this study aimed to investigate the sociodemographic and lifestyle factors that predispose South African taxi drivers who work in the Cape Town Metropole area to the risk of developing MetS. Methods: This cross-sectional study used a convenient sampling method that included 185 male minibus taxi drivers aged 20 years or above. The participants were interviewed using a validated questionnaire to gather information regarding their sociodemographic characteristics and lifestyle practices. They also underwent physical and metabolic assessments, and the International Diabetes Federation (IDF) criteria were used to diagnose people with MetS. Results: Overall, the mean age and driving experience of the taxi drivers were 40.0 years (SD: 10.7) and 9.1 years (SD: 7.4), respectively, with those with MetS being significantly older and having more driving experience than those without. Older participants were 3 and 2.9 times more likely to be diagnosed with MetS than the younger participants. Most taxi drivers (70%) met the IDF diagnostic criteria for MetS. Smokers, those who spent more than 100 ZAR (USD 5.9) and those who spent less than 1.4 MET-minutes per week on physical activity were 1.96, 2.0, and 13.6 times more likely to suffer from MetS that those who were nonsmokers, those who spent less than 100 ZAR and those who spent <1.4 MET-minutes per week on physical activity. Consumption of alcohol and sugar-sweetened beverages (SSBs), as well as takeaway and fried foods, snacks, and sold by the SF vendors, increased the likelihood of developing MetS, abnormal HDL-C, TG, and hypertension, while avoiding takeaway and fried foods decreased this likelihood. Taxi drivers who also avoided consuming fresh fruits had abnormal HDL-C. Conclusion: These findings have significant public health implications, highlighting the need for South African policymakers to adopt a system-level approach to promote lifestyle changes among taxi drivers within the taxi industry. This can help reduce the health risks faced by these drivers and improve their overall health profile.

Classification of Obesity among South African Female Adolescents: Comparative Analysis of Logistic Regression and Random Forest Algorithms.

BACKGROUND: This study evaluates the performance of logistic regression (LR) and random forest (RF) algorithms to model obesity among female adolescents in South Africa. METHODS: Data was analysed on 375 females aged 15-17 from the South African National Health and Nutrition Examination Survey 2011/2012. The primary outcome was obesity, defined as body mass index (BMI) ≥ 30 kg/m2. A total of 31 explanatory variables were included, ranging from socio-economic, demographic, family history, dietary and health behaviour. RF and LR models were run using imbalanced data as well as after oversampling, undersampling, and hybrid sampling of the data. RESULTS: Using the imbalanced data, the RF model performed better with higher precision, recall, F1 score, and balanced accuracy. Balanced accuracy was highest with the hybrid data (0.618 for RF and 0.668 for LR). Using the hybrid balanced data, the RF model performed better (F1-score = 0.940 for RF vs. 0.798 for LR). CONCLUSION: The model with the highest overall performance metrics was the RF model both before balancing the data and after applying hybrid balancing. Future work would benefit from using larger datasets on adolescent female obesity to assess the robustness of the models.

Association between Macronutrient and Fatty Acid Consumption and Metabolic Syndrome: A South African Taxi Driver Survey.

We aimed to examine the association between macronutrient and fatty acid intake and metabolic syndrome (MetS) and its components in South African male mini-bus taxi drivers. One hundred and eighty-five (n = 185) male taxi drivers, aged 20 years and older, who operate in the Cape Town metropole, South Africa, were included. The International Diabetes Federation (IDF) algorithm was used to define MetS. The association between macronutrient and fatty acid intake (assessed using 24 h recall) and MetS were analyzed using multivariable nutrient density substitution models. Overall, protein consumption significantly increased the likelihood of high blood pressure (HBP) and significantly lowered the likelihood of having low levels of high-density lipoprotein cholesterol (HDL-C). In an isoenergetic state, the intake of protein instead of carbohydrates (CHOs) and total fat, reduced the likelihood of elevated triglycerides by 6.7% and 6.6%, respectively. The intake of CHOs instead of protein and total fat, reduced the likelihood of HBP by 2.2% and 2.8%, respectively. In the same isoenergetic state, the intake of saturated fatty acids (SFAs) instead of mono-unsaturated fatty acids (MUFAs) increased the likelihood of HBP by 9.8%, whereas the intake of polyunsaturated fatty acids (PUFAs) instead of SFAs decreased the likelihood of HBP by 9.4%. The current study showed that when total food energy intake is kept constant, a diet that is high in protein, CHOs and PUFAs reduces triglycerides and BP, whereas the intake of total fat and SFAs had the opposite effect. It should, however, be noted that these outcomes were produced using mathematical models, as such we recommend further prospective studies in real life that will reveal the actual associations between the consumption of macronutrients and fatty acids and MetS and its components.

Anthropometric indices and cut-off points for screening of metabolic syndrome among South African taxi drivers.

Background: Detecting the early onset of metabolic syndrome (MetS) allows for quick intervention which may slow progression to a variety of health consequences, hence, determining the best measurement to detect MetS is essential. Aim: This research aimed at examining the MetS predictive power of anthropometric indices, such as body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), body shape index (ABSI), body roundness index (BRI), percentage body fat (%BF), conicity index (CI), and Clínica Universidad de Navarra-body adiposity estimator (CUN-BAE) to determine the cut-off points to identify male South African taxi drivers with MetS. Method: A cross-sectional study was conducted among 185 male taxi drivers. Their weight, height, WC, blood lipid profile were measured. International Diabetes Federation (IDF) definition was used to define MetS. Receiver Operating Characteristic (ROC) curves were used to compare the predictive ability of Anthropometric indices to detect MetS. Results: The mean age of the participants was 39.84 years. Overall, 41.6% (N = 77) of the participants presented with MetS. The mean values for BMI, WC, WHtR, %BF, BRI, CUN-BAE, ABSI and CI were 28.60 ± 6.20 kg/m2, 99.13 ± 17.59 cm, 0.58 ± 0.10, 27.28 ± 8.28%, 5.09 ± 2.33, 27.78 ± 8.34, 0.08 ± 0.01 and 1.70 ± 0.19, respectively. The mean values for these indices were significantly (p < 0.001) higher in participants with MetS. The highest area under the curve (AUC) outcomes for screening MetS were for the %BF and CUN-BAE, followed by the BMI and WHtR, and lastly the BRI. All these anthropometric indices had outstanding discriminatory powers for predicting MetS with AUCs and sensitivity values above 80%. The BMI, WHtR, %BF, BRI, and CUN-BAE, had cut-off points for detection of metS in South African men at 28.25 kg/m2, 0.55, 25.29%, 4.55, and 27.10, respectively. Based on the logistic regression models abnormal BMI, WHtR, %BF, BRI, CUN-BAE, TG, FBG, systolic BP, diastolic BP and WC showed increased risk of MetS. Conclusion: While the %BF, CUN-BAE, BMI, WC, WHtR, BRI, CI and CUN-BAE could predict MetS among South African male taxi drivers, these indices were less effective in predicting the individual MetS risk factors such as TG, BP, and FBG.

Anthropometric indices for predicting cardiovascular risk factors: Ellisras longitudinal study.

OBJECTIVES: The aim of the study was to determine which anthropometric indices can best predict the presence of common cardiovascular risk factors among young adults in the rural village of Ellisras in the Limpopo Province, South Africa. METHODS: A total of 624 young adults (306 males and 318 females) aged 18 to 29 years took part in this cross-sectional study. Anthropometrics were measured according to the standard procedures. Blood pressure and blood parameters were collected and measured. The stepwise logistic regression was used to determine anthropometric indices that can predict the presence of common cardiovascular risk factors and a receiver-operating characteristic (ROC) curve was plotted to assess discrimination abilities of anthropometric indices for cardiovascular risk factors. RESULTS: The waist-to-hip ratio (WHR) in multivariable adjusted models was not found to be associated with cardiovascular risk factors compared to body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR). The area below the ROC curve for the abovementioned indices was above 0.62. CONCLUSIONS: The central obesity indices, WC and WHtR, are better predictors of dyslipedemia and hypercholesterolemia, whereas BMI was a better predictor of hypertension among young adults living in rural South Africa between the ages of 18 and 29 years.